ysenarath commited on
Commit
4cc43f8
·
verified ·
1 Parent(s): aa5c702

End of training

Browse files
Files changed (2) hide show
  1. README.md +99 -0
  2. model.safetensors +1 -1
README.md ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: mit
4
+ base_model: FacebookAI/roberta-base
5
+ tags:
6
+ - generated_from_trainer
7
+ datasets:
8
+ - sentiment140
9
+ metrics:
10
+ - accuracy
11
+ - precision
12
+ - recall
13
+ - f1
14
+ model-index:
15
+ - name: roberta-base-sentiment140
16
+ results:
17
+ - task:
18
+ name: Text Classification
19
+ type: text-classification
20
+ dataset:
21
+ name: sentiment140
22
+ type: sentiment140
23
+ config: sentiment140
24
+ split: train
25
+ args: sentiment140
26
+ metrics:
27
+ - name: Accuracy
28
+ type: accuracy
29
+ value: 0.883
30
+ - name: Precision
31
+ type: precision
32
+ value: 0.8801652892561983
33
+ - name: Recall
34
+ type: recall
35
+ value: 0.8783505154639175
36
+ - name: F1
37
+ type: f1
38
+ value: 0.8792569659442725
39
+ ---
40
+
41
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
42
+ should probably proofread and complete it, then remove this comment. -->
43
+
44
+ # roberta-base-sentiment140
45
+
46
+ This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the sentiment140 dataset.
47
+ It achieves the following results on the evaluation set:
48
+ - Loss: 0.3988
49
+ - Accuracy: 0.883
50
+ - Roc Auc: 0.9515
51
+ - Precision: 0.8802
52
+ - Recall: 0.8784
53
+ - F1: 0.8793
54
+
55
+ ## Model description
56
+
57
+ More information needed
58
+
59
+ ## Intended uses & limitations
60
+
61
+ More information needed
62
+
63
+ ## Training and evaluation data
64
+
65
+ More information needed
66
+
67
+ ## Training procedure
68
+
69
+ ### Training hyperparameters
70
+
71
+ The following hyperparameters were used during training:
72
+ - learning_rate: 2e-05
73
+ - train_batch_size: 32
74
+ - eval_batch_size: 64
75
+ - seed: 42
76
+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
77
+ - lr_scheduler_type: linear
78
+ - lr_scheduler_warmup_ratio: 0.1
79
+ - num_epochs: 10
80
+
81
+ ### Training results
82
+
83
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Roc Auc | Precision | Recall | F1 |
84
+ |:-------------:|:-----:|:------:|:---------------:|:--------:|:-------:|:---------:|:------:|:------:|
85
+ | 0.2864 | 1.0 | 49969 | 0.3030 | 0.777 | 0.9470 | 0.6921 | 0.9732 | 0.8089 |
86
+ | 0.255 | 2.0 | 99938 | 0.2872 | 0.885 | 0.9553 | 0.8585 | 0.9134 | 0.8851 |
87
+ | 0.239 | 3.0 | 149907 | 0.2921 | 0.881 | 0.9543 | 0.8690 | 0.8887 | 0.8787 |
88
+ | 0.2042 | 4.0 | 199876 | 0.3028 | 0.891 | 0.9549 | 0.8821 | 0.8948 | 0.8884 |
89
+ | 0.187 | 5.0 | 249845 | 0.3192 | 0.89 | 0.9536 | 0.8788 | 0.8969 | 0.8878 |
90
+ | 0.1606 | 6.0 | 299814 | 0.3670 | 0.885 | 0.9514 | 0.8715 | 0.8948 | 0.8830 |
91
+ | 0.1343 | 7.0 | 349783 | 0.3988 | 0.883 | 0.9515 | 0.8802 | 0.8784 | 0.8793 |
92
+
93
+
94
+ ### Framework versions
95
+
96
+ - Transformers 4.49.0
97
+ - Pytorch 2.6.0+cu124
98
+ - Datasets 3.3.2
99
+ - Tokenizers 0.21.0
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3e0f486b5837155a8104bb3ee287b07e0186e5f38de74265e61c21fc3e7a3b91
3
  size 498615900
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e7cde7fde420abf5598dd98856df0fa2f592edb0b7f9701e08c02e2759fd1102
3
  size 498615900